The field of the present invention relates to location services. More particularly, the field of the present invention relates to locating a mobile device by noting times of arrival of signals that travel between the mobile device and a plurality of transmitters or receivers located at known positions, and computing a location based on the noted times of arrival.
Recently, the FCC mandated the introduction of location services that can accurately locate wireless subscribers on all wireless networks. Two previously proposed approaches for implementing such location services are the uplink time-of-arrival approach (referred to herein as xe2x80x9cuplinkxe2x80x9d) and the downlink time-of-arrival approach (commonly known as observed time difference or OTD, and referred to herein as xe2x80x9cdownlinkxe2x80x9d).
In the uplink approach, the mobile device (also referred to as a xe2x80x9chandsetxe2x80x9d or xe2x80x9cremote terminalxe2x80x9d) that is to be located sends out a signal. For example, in the context of a GSM system (global system for mobile communication), this signal could be a random access channel (RACH) burst. In other contexts, other signals that are transmitted by the handset may be used. The time of arrival (TOA) of the signal is determined at each of a plurality of location measurement units (LMUs), together with an associated indicator ("sgr") that describes the quality of the TOA measurement. Each of these noted TOAs and "sgr"s is then sent to a computer. The computer then uses conventional algorithms, which are well known to those skilled in the art, to determine the location of the mobile device based on the TOA and "sgr" determinations made by the LMUs and the known location of the LMUs.
One suitable conventional location algorithm uses a Taylor search to locate the intersection of two or more hyperbolas. Details of a such an algorithm can be found in xe2x80x9cStatistical Theory of Passive Location Systemsxe2x80x9d by D. J. Torrieri, IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-20, No. 2, March 1984, which is incorporated herein by reference and is an indication of the existing level of skill in the art. This algorithm locates the mobile device based on three or more TOA readings (which are used to determine the distance from the mobile device to the LMU based on the speed c of the signal), the associated "sgr"s, and the known locations of each LMU. When four or more TOA readings are available, this algorithm can locate the mobile device in three-dimensional space.
In the downlink approach, each of a plurality of base stations (BTSs) sends a signal to the mobile device to be located, and the mobile device determines the TOA and "sgr" of each of these signals. These TOAs and "sgr"s are then transmitted to a remote computer, which implements a conventional algorithm to determine the mobile device""s location based on the TOAs and "sgr", similar to the uplink type systems. Alternatively, if sufficient processing power is available in the handset, the algorithm may be implemented in the handset. When the transmission frames of the BTSs are not synchronized, the downlink algorithms are somewhat more complex because the computer must obtain the relative time difference between each BTS transmission to calculate a location. This relative time information can be obtained using auxiliary receivers located at known locations to measure the TOAs of the signals from the BTSs, in a conventional manner.
In both uplink and downlink systems, three TOA measurements are sufficient to form a location estimate in two-dimensional space (e.g., on the surface of the earth, by assuming sufficient flatness). The accuracy of the location estimate, however, is limited by the resolution and accuracy of the TOA measurements, as well as by noise, interference, and multipath distortion that can corrupt the TOA measurements.
Using more than three TOAs (e.g., using 4-7 TOAs) to form the location estimate can provide improved accuracy, as compared to estimates based on only three TOAs. Unfortunately, in order to include additional TOA measurements, it is often necessary to rely on TOA readings with poor quality communication links. The poor quality of these communication links can counteract some or all of the benefits provided by the additional TOA measurements. In certain circumstances, a location estimate based on four or more TOA measurements may be even worse than an estimate based on only three TOA measurements.
The inventor has recognized a need to improve the accuracy of computed location estimates.
The present invention relates to forming more accurate location estimates by basing the estimates on a good set of TOA measurements.
One aspect of the present invention is directed to a method of locating a mobile device. In this method, a plurality of TOA measurements for communications between the mobile device and at least four fixed stations are obtained, and subsets of these TOA measurements are identified. Then, the accuracy for a location estimate corresponding to each of the identified subsets is predicted. At least one of the subsets is selected based on the predicted accuracy, and a location estimate is formed based on the selected subset or subsets.
Another aspect of the present invention is directed to a method of locating a mobile device. In this method, a plurality of TOA measurements for communications between the mobile device and at least four fixed stations are obtained, and subsets of these TOA measurements are identified. Then, a preliminary location estimate is formed for each subset and an accuracy is determined for each preliminary location estimate. At least one of the preliminary location estimates is selected based on the determined accuracy, and a final location estimate is formed based on the selected preliminary location estimate or estimates.
Another aspect of the present invention is directed to a method of locating a mobile device. In this method, a plurality of TOA measurements are obtained. A geometric dilution of precision (GDOP) of an expected solution geometry for subsets of these TOA measurements is predicted based on (a) an estimate of a location of the mobile device and (b) known locations of fixed stations corresponding to the TOA measurements. A subset of TOA measurements is selected based on the GDOP predictions, and a location estimate is computed based on the TOA measurements in the selected subset.
Another aspect of the present invention is directed to a method of locating a mobile device. In this method, a plurality of TOA measurements are obtained, and a plurality of subsets of these TOA measurements are identified. A preliminary location estimate is computed for each of the identified subsets, and a GDOP of a solution geometry is determined for each preliminary location estimate. This GDOP is determined based on (a) the respective preliminary location estimate and (b) known locations of fixed stations corresponding to the TOA measurements that were used to form each preliminary location estimate. Based on the determined GDOPs, a particular subset of TOA measurements is selected. A location estimate is then computed based on the TOA measurements in the selected subset.
Another aspect of the present invention is directed to a method of locating a mobile device. In this method, at least four TOA measurements are obtained. A subset of three of these TOA measurements is selected. Based on this subset, a preliminary location estimate is formed using a closed-form algorithm. A final location estimate is then computed using an open-form algorithm, using the preliminary location estimate to initialize the open-form algorithm.